Project Summary/Abstract: Approximately 13 million Americans suffer from age-related dysphonia, a communication disorder resulting in hoarseness and weak voice. Communication difficulty places older adults at increased risk for mental and physical health problems, and dysphonia specifically interferes with the ability to participate in the work force and to be heard and understood when speaking in noisy environments and over the phone. Despite the importance of successful treatment of age-related dysphonia, voice therapy and surgery improve voice for a just small fraction of patients. A key barrier to improving treatment algorithms in age-related dysphonia is lack of knowledge about how voice therapy techniques change voice and which factors moderate that improvement. The objectives for this application are to determine the mechanisms by which specific therapy tasks improve voice in age-related dysphonia, and the conditions that limit the extent of improvement. The aims are directed at understanding the physics of voice therapies, aspects that can be studied with physiological data collected from voice users combined with theoretical and computational models. The Specific Aims are: (1) To determine how therapy tasks that modify respiration, vocal function, and vocal tract shape alter vocal fold vibration in older adults with age-related dysphonia, and (2) To determine through computational modeling how modifications to respiratory and vocal tract parameters alter glottal flow, the acoustic signal, and voice quality. In Aim 1, we will use laryngeal high-speed videoendoscopy to measure the changes to vocal fold kinematics as participants complete several voice therapy tasks. In Aim 2, we will personalize a computational vocal tract model to a subset of participants from Aim 1 in order to simulate incremental changes to individual airflow and vocal tract parameters and combinations of the parameters. Results will be analyzed using aerodynamic, acoustic, and perceptual measures. Taken together, the studies will provide the information necessary to determine the mechanisms by which specific tasks improve vocal function and voice quality. The results will be used to generate a matrix showing the extent of improvement to vocal fold vibration, acoustic measures, and voice quality with each therapy task or combination of tasks for a given severity level. The matrix will provide guidance for therapy planning based on initial patient presentation and will provide direction for novel therapies in the future. The resulting algorithm will be tested using human subjects in future work.